Abstract: A method and system for inspecting a structure are disclosed. Data is obtained from a dimensional sensor such as a LIDAR, RGBD, or other sensor capable of collecting data in three dimensions to define a structure element or object, describing physical dimensions of a structure and its elements. A verbal description is obtained with an audio sensor. Machine learning (ML) engines identify the elements of the structure and its physical features. Audio data is parsed using NLP techniques to identify additional attributes such as the material composition of identified elements. An anomaly assessment ML engine processes the identified elements and the material composition data to determine damage or compliance status of each structure element, and financial estimation ML engine determines a financial value attributable to a structure element having the identified anomaly type(s).